Artificial Analysis Intelligence Index v4.3
Muse Wonder Full 56.0 leads since October 2026 Version 4.3 of Artificial Analysis's index, eleven weighted parts led by knowledge work, office tasks and Terminal-Bench 4.0.
Released 7 September 2026 and in use until 27 October 2026, with 4.3.1 (new pairwise judge panels) and 4.3.2 (Crowd-BT Elo fitting for GDPval-AA v2.1 and AA-Briefcase v1.1). Weights: GDPval-AA v2 10%, AA-Briefcase 15%, AutomationBench-AA 5%, Terminal-Bench 4.0 10%, SciCode 10%, AA-LCR 5%, AA-Omniscience accuracy 10% and non-hallucination 5%, Humanity's Last Exam 10%, GDP.pdf 10%, CritPt 10%.
- Made by
- Artificial Analysis
- Released
- September 2026
- Kind
- Composite indices
- Scored
- Checked automatically
- Answers
- Agent task
- Strongest model tested
- Muse Wonder #15 on the capability index
- Last in a launch post
- October 2026
- Last model added
- October 2026
Muse Wonder Full leads with 56.0
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
- 1 Muse Wonder Full 56.0
- 2 Muse Wonder 52.0
- 3 Muse Spark Open 39.0
- 4
Solar Mini 4 24.1
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Muse Wonder Full | 56.0 | Oct 2026 | Lab model card | |
| 2 | Muse Wonder | 52.0 | Oct 2026 | Lab model card | |
| 3 | Muse Spark Open | 39.0 | Oct 2026 | Lab model card | |
| 4 | Solar Mini 4 | 24.1 | Oct 2026 | Lab model card |
2 models have held number one in labs’ own numbers since its release in September 2026
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Labs’ model cards
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
2 labs put it in a launch post in the last six months
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Oct 15, 2026 | Muse Spark Open | 39 | Artificial Analysis Intelligence Index |
| Oct 12, 2026 | Muse Wonder | 52 | Artificial Analysis Index |
| Oct 12, 2026 | Muse Wonder Full | 56 | Artificial Analysis Index |
| Oct 1, 2026 | Solar Mini 4 | 24.1 | Artificial Analysis Intelligence Index v4.3.2 |
2 system cards report it, from 1 lab
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Oct 12, 2026 | Muse Wonder model card | 52 | Artificial Analysis Index (AA Intelligence Index v4.3 in the methodology text), Muse Wonder (max) (capabilities table image, page 3) | Capabilities |
| Oct 12, 2026 | Muse Wonder Full model card | 56 | Artificial Analysis Index (AA Intelligence Index v4.3 in the methodology text), Muse Wonder Full (max) (capabilities table image, page 3) | Capabilities |
Versions
More in Other
- Personal Superintelligence Index (Meta) In use Meta's composite of seven personal and knowledge-work evals: Agents' Last Exam, AutomationBench-AA, FocusBench, JobBench, GDP.pdf, VBT and DRACO.
- SAGE v1.1 (Vals) In use Models grade handwritten undergraduate math and computer science work against rubrics. Scored by class-balanced accuracy of each rubric check against expert grading. Claude Opus 5.5 91.3%
- MTEB Fading Massive Text Embedding Benchmark: retrieval, clustering, classification across languages and modalities.
sonar 42% - Anthropic ECI (AECI) Only in system cards Index that combines a basket of capability benchmarks into one capability score to track trends across Anthropic models. Claude Opus 5.5 169.4
- SPEED-Bench Only in system cards Measures speculative decoding across varied prompts and domains. Reports the average acceptance length of draft tokens, so higher means faster generation at the same output.
Nemotron 3 Ultra 5.15 - Qwen in-house English automatic evaluation Only in system cards Models answer Qwen in-house English datasets on knowledge, comprehension, coding, math and related skills. Skills and weights change between reports.
Qwen2-72B 72.9%